code: def test_get_feature_names_out(df_na):
      original_features = df_na.columns.to_list()
  
      tr = AddMissingIndicator(missing_only=False)
      tr.fit(df_na)
  
      out = [f + "_na" for f in original_features]
      feat_out = original_features + out
  
      assert tr.get_feature_names_out(input_features=None) == feat_out
      assert (
          tr.get_feature_names_out(input_features=original_features)
          == feat_out
      )
  
      tr = AddMissingIndicator(missing_only=True)
      tr.fit(df_na)
  
      out = [f + "_na" for f in original_features[0:-1]]
      feat_out = original_features + out
  
      assert tr.get_feature_names_out(input_features=None) == feat_out
      assert (
          tr.get_feature_names_out(input_features=original_features)
          == feat_out
      )
  
      with pytest.raises(ValueError):
          tr.get_feature_names_out("Name")
  
      with pytest.raises(ValueError):
          tr.get_feature_names_out(["Name", "hola"])
  
file_path: feature_engine/tests/test_imputation/test_missing_indicator.py
imports: import pytest
  from sklearn.pipeline import Pipeline
  from feature_engine.imputation import AddMissingIndicator
label_desc: Use image node_id 6 for calling a global function with example usage: test_get_feature_names_out(df_na) without return types